Despite the fact that humans haven’t returned to the Moon since the cancellation of the Apollo program in 1972, there have nonetheless been incredible advances in space exploration in recent years. All across the world, human time is the most valuable commodity – particularly when it comes to solving problems. Far from stealing jobs, the majority of advances in artificial intelligence and machine learning are designed to automate relatively “simple” processes and free up time for humans to do ...

Despite the fact that humans haven’t returned to the Moon since the cancellation of the Apollo program in 1972, there have nonetheless been incredible advances in space exploration in recent years. All across the world, human time is the most valuable commodity – particularly when it comes to solving problems. Far from stealing jobs, the majority of advances in artificial intelligence and machine learning are designed to automate relatively “simple” processes and free up time for humans to do what they do best.

Already we have had a taste of what AI can achieve from space, even as far back as the early 2000s with the launch of the Earth Observing-1 (EO-1) satellite, which helps analyse and inform the appropriate response in the event of a disaster, such as hurricanes and volcanic eruptions. In some cases, the systems in place on EO-1 began capturing satellite images of disaster zones before ground personnel were even aware that a disaster had occurred. More recently, AI has been used on the Mars Curiosity rover, where AEGIS software is able to identify intriguing rock or soil patches that should be targeted for analysis. This significantly expedites the process of collecting data from the surface of Mars as the robot isn’t relying solely on human commands.

Richard Branson’s Virgin Galactic – which hopes to soon begin conducting commercial flights – charges between $200,000 to $250,000 per ticket for a flight where passengers will experience just several minutes of weightlessness beyond the Karman line where space officially begins. Therefore, previous space missions have always needed to consider very carefully which astronauts they send to space, with the ultimate decision often coming down to an astronaut’s ability to act as a ‘jack-of-all-trade’. In future, it should be possible to automate the computing and engineering tasks that historically astronauts have had to train for. This would mean sending individuals with specialised expertise in science and research in place of the all-rounder astronauts of yesteryear.

For success in space exploration in the years to come, we will need to continue along the exponential curve of open source uptake and see advances in the approach to how spacecraft software, hardware and infrastructure is developed and deployed. With this baseline in place, advances in AI-driven scientific research have the potential to propel us forwards.

(Source: https://www.scitecheuropa.eu/)

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